Traits Measuring Metrics for the Members of Semantic Social Network

Semantic social network (SSN) is an extension of the current social network wherein meaningful data is added with each piece of information, known as metadata. This metadata is processed by machines to make decisions based on intelligent algorithms. SSN gives a virtual social circle where individuals can share information, ideas, news and stay connected with their friends and family. The semantic social information can be used to measure various behavioral traits of SSN individuals using metrics. There are several metrics developed to calculate the individual’s traits of the semantic social network. However, few metrics may produce wrong results in the absence of time consideration during their calculations. In this article, we have proposed a novel technique to improve the accuracy of activity factor metric calculation and another metric to calculate peak active time for an activity. The extracted results from our novel SSN metrics can help authorities to make better decisions in providing offers, rewards, suggestions, and badges for the SSN members as per their needs and interests.